Filip P. Paszkiewicz
Papers
1
Total Citations
2
H-Index
1
About
Filip P. Paszkiewicz is a researcher focused on advancing lower-limb prosthetics through intelligent signal processing and human-machine interaction. His primary research areas include mechanomyography (MMG), gait intent classification, and subject-independent data pooling for prosthetic control systems. Paszkiewicz’s major contribution lies in developing methods to classify gait modes using MMG signals from residual muscles in transtibial amputees, reducing reliance on delayed feedback from inertial measurement units. His work demonstrates that pooled data from multiple subjects can improve classifier robustness, a key step toward more responsive and adaptive prosthetic devices. Although his most-cited paper has garnered 2 citations, its significance lies in addressing a critical bottleneck in active prosthetics: the need for terrain-adaptive control without movement-dependent delays. This foundational work has implications for expanding patient mobility across varied environments. Paszkiewicz’s research represents an important step toward seamless, intuitive prosthetic control that anticipates user intent, ultimately aiming to enhance quality of life for individuals with limb loss.
Research Focus
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Top Papers
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